ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Strong Motion Data Based Regional Ground Motion Prediction Equations for North East India Based on Non-Linear Regression Models

Ramkrishnan, R and Sreevalsa, K and Sitharam, TG (2020) Strong Motion Data Based Regional Ground Motion Prediction Equations for North East India Based on Non-Linear Regression Models. In: Journal of Earthquake Engineering, 26 (6). 2927 -2947.

[img] PDF
jour_ear_eng_ramakrishnan.pdf - Published Version
Restricted to Registered users only

Download (5MB) | Request a copy
Official URL: https://doi.org/10.1080/13632469.2020.1778586

Abstract

Existing Ground Motion Prediction Equations (GMPE) in practice for North East India have been developed using limited or simulated datasets of recorded ground motions. The current study presents the development of a new GMPE based on a well-established model considering actual recorded ground motion data comprising of acceleration, magnitude, and hypocentral distances. A larger dataset with magnitudes ranging from 4.2 to 6.9 and up to 640 kms, with a total of 204 recordings is used in non-linear multiple-regression. The newly developed GMPE could predict ground acceleration realistically over larger ranges of distance and magnitudes, compared to existing GMPEs. © 2020, © 2020 Taylor & Francis Group, LLC.

Item Type: Journal Article
Publication: Journal of Earthquake Engineering
Publisher: Taylor and Francis Ltd.
Additional Information: Copyright to this article belongs to Taylor and Francis.
Keywords: Earthquake effects; Equations of motion; Forecasting; Logistic regression, Ground accelerations; Ground motions; Ground-motion prediction equations; Hypocentral distance; Non-linear regression; North- East India; Simulated datasets; Strong motion datum, Motion estimation
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Date Deposited: 10 Nov 2021 15:57
Last Modified: 21 Sep 2022 06:56
URI: https://eprints.iisc.ac.in/id/eprint/66004

Actions (login required)

View Item View Item